Anomaly detection in images can be divided into two broad classes (among others) [1]}, [2]}: direct inference/classification of anomalies [3]}, [4]}, [5]}; and reconstruction and comparison based anomaly detection (typically un/semi-supervised) [6]}, [7]}, [8]}.
Bergmann et al. [9]} examined SSIM as a distance metric for autoencoder reconstruction anomaly detection, which yielded results similar to L2.
In our work, we focus on a PCA reconstruction based anomaly detection setup where we examine the applicability of PSE as a distance metric.
